





'''simple docstring'''



import glob
import os
import random
from string import ascii_lowercase, digits

import cva
_SCREAMING_SNAKE_CASE       =     ""
_SCREAMING_SNAKE_CASE       =     ""
_SCREAMING_SNAKE_CASE       =     ""
_SCREAMING_SNAKE_CASE       =     1  # (0 is vertical, 1 is horizontal)




def  _lowerCAmelCase    (					):
			__lowercase    ,		__lowercase					    =				get_dataset(UpperCamelCase_		,							UpperCamelCase_					)
			print('''Processing...'''					)
			__lowercase    ,		__lowercase    ,		__lowercase					    =				update_image_and_anno(UpperCamelCase_		,							UpperCamelCase_		,							UpperCamelCase_					)

			for index, image in enumerate(UpperCamelCase_					):
						# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
						__lowercase					    =				random_chars(3_2					)
						__lowercase					    =				paths[index].split(os.sep					)[-1].rsplit('''.'''		,							1					)[0]
						__lowercase					    =				f"{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}"
						cva.imwrite(f"/{file_root}.jpg"		,							UpperCamelCase_		,							[cva.IMWRITE_JPEG_QUALITY, 8_5]					)
						print(f"Success {index+1}/{len(UpperCamelCase_					)} with {file_name}"					)
						__lowercase					    =				[]
						for anno in new_annos[index]:
									__lowercase					    =				f"{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}"
									annos_list.append(UpperCamelCase_					)
						with open(f"/{file_root}.txt"		,							'''w'''					) as outfile:
									outfile.write('''\n'''.join(line for line in annos_list					)					)




def  _lowerCAmelCase    (					lowerCamelCase_      :	List[Any]		,							lowerCamelCase_      :	List[str]					):
			__lowercase					    =				[]
			__lowercase					    =				[]
			for label_file in glob.glob(os.path.join(UpperCamelCase_		,							'''*.txt'''					)					):
						__lowercase					    =				label_file.split(os.sep					)[-1].rsplit('''.'''		,							1					)[0]
						with open(UpperCamelCase_					) as in_file:
									__lowercase					    =				in_file.readlines()
						__lowercase					    =				os.path.join(UpperCamelCase_		,							f"{label_name}.jpg"					)

						__lowercase					    =				[]
						for obj_list in obj_lists:
									__lowercase					    =				obj_list.rstrip('''\n'''					).split(''' '''					)
									boxes.append(
									    [
									        int(obj[0]					),
									        float(obj[1]					),
									        float(obj[2]					),
									        float(obj[3]					),
									        float(obj[4]					),
									    ]					)
						if not boxes:
									continue
						img_paths.append(UpperCamelCase_					)
						labels.append(UpperCamelCase_					)
			return img_paths, labels




def  _lowerCAmelCase    (					lowerCamelCase_      :	int		,							lowerCamelCase_      :	Union[str, Any]		,							lowerCamelCase_      :	Optional[int] = 1					):
			__lowercase					    =				[]
			__lowercase					    =				[]
			__lowercase					    =				[]
			for idx in range(len(UpperCamelCase_					)					):
						__lowercase					    =				[]
						__lowercase					    =				img_list[idx]
						path_list.append(UpperCamelCase_					)
						__lowercase					    =				anno_list[idx]
						__lowercase					    =				cva.imread(UpperCamelCase_					)
						if flip_type == 1:
									__lowercase					    =				cva.flip(UpperCamelCase_		,							UpperCamelCase_					)
									for bbox in img_annos:
												__lowercase					    =				1 - bbox[1]
												new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]					)
						elif flip_type == 0:
									__lowercase					    =				cva.flip(UpperCamelCase_		,							UpperCamelCase_					)
									for bbox in img_annos:
												__lowercase					    =				1 - bbox[2]
												new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]					)
						new_annos_lists.append(UpperCamelCase_					)
						new_imgs_list.append(UpperCamelCase_					)
			return new_imgs_list, new_annos_lists, path_list




def  _lowerCAmelCase    (					lowerCamelCase_      :	Dict = 3_2					):
			assert number_char > 1, "The number of character should greater than 1"
			__lowercase					    =				ascii_lowercase + digits
			return "".join(random.choice(UpperCamelCase_					) for _ in range(UpperCamelCase_					)					)


if __name__ == "__main__":
	main()
	print('''DONE ✅''')









import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
 from PIL import Image

 from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor

@require_vision
class     A__   (       unittest.TestCase      ):







    """simple docstring"""

    def 						a_     (			self       ):
         snake_case											=							tempfile.mkdtemp()

         snake_case											=							[
             '''[UNK]''',
             '''[CLS]''',
             '''[SEP]''',
             '''[PAD]''',
             '''[MASK]''',
             '''的''',
             '''价''',
             '''格''',
             '''是''',
             '''15''',
             '''便''',
             '''alex''',
             '''##andra''',
             '''，''',
             '''。''',
             '''-''',
             '''t''',
             '''shirt''',
         ]
         snake_case											=							os.path.join(self.tmpdirname     ,   VOCAB_FILES_NAMES['''vocab_file''']       )
         with open(self.vocab_file     ,   '''w'''     ,   encoding='''utf-8'''       ) as vocab_writer:
              vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]       )       )

         snake_case											=							{
             '''do_resize''': True,
             '''size''': {'''height''': 2_2_4, '''width''': 2_2_4},
             '''do_center_crop''': True,
             '''crop_size''': {'''height''': 1_8, '''width''': 1_8},
             '''do_normalize''': True,
             '''image_mean''': [0.4814_5466, 0.457_8275, 0.4082_1073],
             '''image_std''': [0.2686_2954, 0.2613_0258, 0.2757_7711],
             '''do_convert_rgb''': True,
         }
         snake_case											=							os.path.join(self.tmpdirname     ,   __snake_case       )
         with open(self.image_processor_file     ,   '''w'''     ,   encoding='''utf-8'''       ) as fp:
              json.dump(__snake_case     ,   __snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return BertTokenizer.from_pretrained(self.tmpdirname     ,   **__snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return BertTokenizerFast.from_pretrained(self.tmpdirname     ,   **__snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname     ,   **__snake_case       )
    def 						a_     (			self       ):
         shutil.rmtree(self.tmpdirname       )
    def 						a_     (			self       ):
         snake_case											=							[np.random.randint(2_5_5     ,   size=(3, 3_0, 4_0_0)     ,   dtype=np.uinta       )]

         snake_case											=							[Image.fromarray(np.moveaxis(__snake_case     ,   0     ,   -1       )       ) for x in image_inputs]

         return image_inputs
    def 						a_     (			self       ):
         snake_case											=							self.get_tokenizer()
         snake_case											=							self.get_rust_tokenizer()
         snake_case											=							self.get_image_processor()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )
         processor_slow.save_pretrained(self.tmpdirname       )
         snake_case											=							ChineseCLIPProcessor.from_pretrained(self.tmpdirname     ,   use_fast=__snake_case       )

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )
         processor_fast.save_pretrained(self.tmpdirname       )
         snake_case											=							ChineseCLIPProcessor.from_pretrained(self.tmpdirname       )

         self.assertEqual(processor_slow.tokenizer.get_vocab()     ,   tokenizer_slow.get_vocab()       )
         self.assertEqual(processor_fast.tokenizer.get_vocab()     ,   tokenizer_fast.get_vocab()       )
         self.assertEqual(tokenizer_slow.get_vocab()     ,   tokenizer_fast.get_vocab()       )
         self.assertIsInstance(processor_slow.tokenizer     ,   __snake_case       )
         self.assertIsInstance(processor_fast.tokenizer     ,   __snake_case       )

         self.assertEqual(processor_slow.image_processor.to_json_string()     ,   image_processor.to_json_string()       )
         self.assertEqual(processor_fast.image_processor.to_json_string()     ,   image_processor.to_json_string()       )
         self.assertIsInstance(processor_slow.image_processor     ,   __snake_case       )
         self.assertIsInstance(processor_fast.image_processor     ,   __snake_case       )
    def 						a_     (			self       ):
         snake_case											=							ChineseCLIPProcessor(tokenizer=self.get_tokenizer()     ,   image_processor=self.get_image_processor()       )
         processor.save_pretrained(self.tmpdirname       )

         snake_case											=							self.get_tokenizer(cls_token='''(CLS)'''     ,   sep_token='''(SEP)'''       )
         snake_case											=							self.get_image_processor(do_normalize=__snake_case       )

         snake_case											=							ChineseCLIPProcessor.from_pretrained(
             self.tmpdirname     ,   cls_token='''(CLS)'''     ,   sep_token='''(SEP)'''     ,   do_normalize=__snake_case       )

         self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer_add_kwargs.get_vocab()       )
         self.assertIsInstance(processor.tokenizer     ,   __snake_case       )

         self.assertEqual(processor.image_processor.to_json_string()     ,   image_processor_add_kwargs.to_json_string()       )
         self.assertIsInstance(processor.image_processor     ,   __snake_case       )
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							self.prepare_image_inputs()

         snake_case											=							image_processor(__snake_case     ,   return_tensors='''np'''       )
         snake_case											=							processor(images=__snake_case     ,   return_tensors='''np'''       )

         for key in input_feat_extract.keys():
              self.assertAlmostEqual(input_feat_extract[key].sum()     ,   input_processor[key].sum()     ,   delta=1E-2       )
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							'''Alexandra，T-shirt的价格是15便士。'''

         snake_case											=							processor(text=__snake_case       )

         snake_case											=							tokenizer(__snake_case       )

         for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key]     ,   encoded_processor[key]       )
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							'''Alexandra，T-shirt的价格是15便士。'''
         snake_case											=							self.prepare_image_inputs()

         snake_case											=							processor(text=__snake_case     ,   images=__snake_case       )

         self.assertListEqual(list(inputs.keys()       )     ,   ['''input_ids''', '''token_type_ids''', '''attention_mask''', '''pixel_values''']       )

         # test if it raises when no input is passed
         with pytest.raises(__snake_case       ):
              processor()
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         snake_case											=							processor.batch_decode(__snake_case       )
         snake_case											=							tokenizer.batch_decode(__snake_case       )

         self.assertListEqual(__snake_case     ,   __snake_case       )




    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							'''Alexandra，T-shirt的价格是15便士。'''
         snake_case											=							self.prepare_image_inputs()

         snake_case											=							processor(text=__snake_case     ,   images=__snake_case       )

         self.assertListEqual(list(inputs.keys()       )     ,   processor.model_input_names       )




